This document summarizes three genomic approaches: 1) Profiling downstream target genes of the Runx3 transcription factor in gastric cancer cells, identifying both up- and downregulated genes. 2) Constructing an shRNA library targeting the mouse kinome to discover regulators of osteogenesis through screening. 3) Investigating the protein interaction between Bmi1 and Pontin52, linking them to hematopoietic stem cell self-renewal and exploring their roles in cancer cell death.

1. Three Functional Genomic Approaches to Biochemical and Screen-Based Analyses of Topics in Cellular Biology Jovana J. Grbi ć Schultz Laboratory April 09, 2007

7. Establishing a Working Cell Line M AGS SNU-1 SNU-16 AZA TSA - - - - - + - + + + - - - + - + + + Runx3 5’-aza-2’- deoxycytidine Demethylation: MS-PCR: runx3 CpG island (~890 bp) F R WT Runx3 sequence AGS (after sodium bisulfite) SNU-1 (after sodium bisulfite) RT-PCR Runx3 1 2 3 4 M

8. Runx3 Profiling Strategy M - + + AGS WT AZA-treated Overexpression AZA treated Over- expression Vector Runx3 β -actin Generate Comprehensive Expression Profile Overlap signatures and Analyze convergent data Extract mRNAs in duplicate Hybridize Onto UA133 Affy Chip Dr. John Walker

9. Runx3 Upregulated Genes 2.02 2.00 transmembrane 4 superfamily member 1 2.51 2.30 beta tubulin, polypeptide 2.10 2.33 parvulin hPar14 2.24 2.33 neuropilin 1 2.52 2.49 tumor necrosis factor receptor superfamily, member 6 2.15 2.49 lipase protein 2.82 2.62 A kinase (PRKA) anchor protein 2 3.25 2.89 Molecule interacting with Rab13 3.54 3.32 solute carrier family 1, member 3 3.37 3.38 solute carrier family 2, member 3 4.54 4.07 hydroxyprostaglandin dehydrogenase 15-(NAD) 4.49 4.92 Sterile alpha motif domain containing 4 (SAMD4) AGS_runx3 AGS+AZA Gene ID

11. Runx3 Downregulated Genes AGS+AZA Runx3 stable • Tumorigenesis and Cancer Progression • Selectively Overexpressed in Cancer • Other Disease Regulatory Roles -2.11 -2.2 NM_001730 Kruppel-like factor 5 (intestinal) -2.23 -2.6 NM_003667 G protein-coupled receptor 49 -2.28 -2.4 NM_002909 REG1α -2.34 -2.1 NM_139273 cysteinyl-tRNA synthetase -2.37 -2.3 NM_000153 galactosylceramidase -2.64 -2.1 NM_015000 STK38L (NDR2) -2.92 -2.9 X54989 Evi-1 -3.11 -3.1 NM_001536 HRMT1L2 -3.44 -3.0 NM_005194 C/EBPβ -3.55 -3.6 NM_003617 regulator of G-protein signalling 5 -5.41 -5.3 NM_004563 phosphoenolpyruvate carboxykinase 2 AGS_runx3 AGS+AZA Accession # Gene ID

16. Algorithmic Sequence Design 5 ’ - CUUACGCUGAGUACUUCGA dTdT dTdT GAAUGCGACUCAUGAAGCU -5’ AGGTGGACATAA CTTA CGCTGAGTACT TCGA TTTGTCCGTTCGG 5’ 3’ CDS 0 1 2 3 4 GC 5 0 1 2 3 4 GC 3 0 4 8 9 12 16 19 GC of the oligo AA 5 TA 4 AT 2 TT 2 NA 1 NN 0 TT 5 TA 4 AT 2 AA 2 TN 1 NN 0 F = W 5 ·F 5 + W 3 ·F 3 + W GC ·F GC + W GC5 ·F GC5 + W GC3 ·F GC3 F 5 F 3 Dr. Serge Batalov (Favorability)

17. Final Sequence Generation 5 unique sequences: Specificity, Fidelity, Ideal Parameters 1) Parameter input 2) Additional algorithm values 3) Putative sequence candidates generated 4) Smith-Waterman similarity search 5) Unique sequences vetted for shDNA cloning

18. High Throughput Library Construction Dr. Anthony Orth, Dr. Sheng Ding, Alicia Linford, Myleen Medina High-throughput mini-preps, plating into 384-well format Primer PCRs Transfection into E.Coli Ligation into pDONR vector Total library consists of 5 siDNA targets per gene, targeting approximately 500 total murine kinases (Approximately 85-90% sequence fidelity)

20. Osteogenesis Screening Alkaline Phosphatase Fluorescence Assay Cbfa1 Reporter Assay 2 rounds of ALP screening and Cbfa1 confirmation: 87 primary hits validated by both methods Dr. Xu Wu

21. Hit Characterization A)

27. IP-MS Design and Execution FLAGActin FLAGBMI-1 WT FLAGActin FLAGBMI1 64 82 48 Anti-FLAG Ab FLAG-Actin FLAG-BMI-1 293T MALDI-TOF Hit picks, etc. *known Bmi-1 interactor † bait protein

29. SymAtlas Expression Correlation BMI-1 Pontin52 c-Myc HSC Progenitors T and B Cells Almost fingerprint-like degree of expression homology, specifically along blood-related cell lineages

30. FLAG bead IP; Anti-Pontin52 Antibody Lane 1 (FLAGActin) Lane 2 (blank) Lane 3 (FLAGBMI1) 85 60 50 BMI-1 interacts with Pontin-52 under native conditions Interaction also verified with co-IP (FLAG BMI and HA Pontin) * *positive control 293T cells: B=Bmi1 A=Actin P=Pontin52 B A P B+A B+P

31. Silencing Confers Cancer Cell Death • Loss of Bmi1 established as incurring apoptosis in cancer cells •Parallel effects with Pontin52??? Knockdown Efficiency